Data visualization means building visual images with computer graphics to help people understand large and complex scientific results and concepts in real life. Visualization technology is especially important in complex network research, which can help to present or interpret complex network data or models, then discover various patterns, characteristics, and relationships.
At present, the process of the data visualization is mainly that debugging and configuring parameters with professional software tools, and then exploring the object of visual results. In the process of current data visualization, it is necessary that professional staffs make tedious data adjustment, comprising adjusting node color, node size, and network shape, etc, thus the workload is heavy and the work is tedious. After the data has been updated, the data has to be re-adjusted by professional staffs, overlapping work is too much and cumbersome, because of which cannot achieve the goal that updating data synchronously. In addition, the duplicated nodes in the current data visualization process makes some nodes cannot be rendered completely, which leads to the unclear topology structure and needs manual reprocessing, thus the work is heavy and tedious and it is not conducive to data visualization efficiency.